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Google Data Engineer Sample Questions:

1. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .

A) conditional node
B) master node
C) worker node
D) application node

2. What are all of the BigQuery operations that Google charges for?

A) Storage, queries, and streaming inserts
B) Storage, queries, and exporting data
C) Storage, queries, and loading data from a file
D) Queries and streaming inserts

3. Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

A) Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
B) Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
C) Introduce data compression for each file to increase the rate file of file transfer.
D) Assemble 1,000 files into a tape archive (TAR) fil
E) Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
F) Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.

4. You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

A) Transform
B) PCollection
C) Pipeline
D) Sink API

5. You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

A) Load the data every 30 minutes into a new partitioned table in BigQuery.
B) Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.
C) Store the data in Google Cloud Datastor
D) Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
E) Store the data in a file in a regional Google Cloud Storage bucke
F) Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery

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